President/Founder, Rozsak Management Consulting, Inc.
I’ve spent time working on projects where I helped train AI systems by reviewing and labeling data, making sure the outputs were accurate, consistent, and actually made sense in context. A lot of the work involved reading through responses, checking them against guidelines, and deciding whether they met the standard—or needed to be corrected. Beyond basic labeling, I was often looking at the nuance of how something was written—tone, clarity, and whether it would feel natural to a real person. When something was off, I’d flag it and help refine it so the response was more useful and aligned with what was being asked. I also started to notice patterns in where things would go wrong, which made it easier to catch issues early and apply the guidelines more consistently. It’s detail-heavy work, but I enjoy it because it sits right at the intersection of structure and judgment—you have to follow rules, but you also have to think. Over time, I got comfortable working with evolving instructions and maintaining a high level of quality, even as the expectations shifted.